pb-dispatching-parallel-agents

name	pb-dispatching-parallel-agents
description	Use when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies

pb-dispatching-parallel-agents

You delegate tasks to specialized agents with isolated context. By precisely crafting their instructions and context, you ensure they stay focused and succeed at their task. They should never inherit your session's context or history — you construct exactly what they need. This also preserves your own context for coordination work.

Core principle: Dispatch one agent per independent problem domain. Let them work concurrently.

When to Use

Use when:

• 3+ test files failing with different root causes
• Multiple subsystems broken independently
• Each problem can be understood without context from others
• No shared state between investigations

Don't use when:

• Failures are related (fix one might fix others)
• Need to understand full system state
• Agents would interfere with each other

The Pattern

1. Identify Independent Domains

Group failures by what's broken:

• File A tests: Tool approval flow
• File B tests: Batch completion behavior
• File C tests: Abort functionality

Each domain is independent — fixing tool approval doesn't affect abort tests.

2. Create Focused Agent Tasks

Each agent gets:

• Specific scope: One test file or subsystem
• Clear goal: Make these tests pass
• Constraints: Don't change other code
• Expected output: Summary of what you found and fixed

3. Dispatch in Parallel

Task("Fix agent-tool-abort.test.ts failures")
Task("Fix batch-completion-behavior.test.ts failures")
Task("Fix tool-approval-race-conditions.test.ts failures")
// All three run concurrently

Multiple dispatch calls in one response = parallel execution. One per response = sequential.

4. Review and Integrate

When agents return:

• Read each summary
• Verify fixes don't conflict
• Run full test suite: uv run pytest
• Integrate all changes

Agent Prompt Structure

Good agent prompts are:

1. Focused — One clear problem domain
2. Self-contained — All context needed to understand the problem
3. Specific about output — What should the agent return?

Fix the 3 failing tests in tests/test_abort.py:

1. "test_abort_tool_with_partial_output" - expects 'interrupted at' in message
2. "test_mixed_completed_and_aborted" - fast tool aborted instead of completed
3. "test_pending_count_tracking" - expects 3 results but gets 0

Your task:

1. Read the test file and understand what each test verifies
2. Identify root cause
3. Fix the issue
4. Run tests to confirm

Do NOT just increase timeouts — find the real issue.

Return: Summary of what you found and what you fixed.

Common Mistakes

❌ Too broad: "Fix all the tests" — agent gets lost ✅ Specific: "Fix test_abort.py" — focused scope

❌ No context: "Fix the race condition" — agent doesn't know where ✅ Context: Paste the error messages and test names

❌ No constraints: Agent might refactor everything ✅ Constraints: "Do NOT change production code" or "Fix tests only"

❌ Vague output: "Fix it" — you don't know what changed ✅ Specific: "Return summary of root cause and changes"

When NOT to Use

• Related failures: Fixing one might fix others — investigate together first
• Need full context: Understanding requires seeing entire system
• Exploratory debugging: You don't know what's broken yet
• Shared state: Agents would interfere (editing same files, using same resources)

Verification

After all agents complete and you integrate changes:

1. Run full test suite
2. Check for merge conflicts
3. Verify no regressions introduced
4. Spot-check key files for correctness

Real Example from Session

Scenario: 6 test failures across 3 files after major refactoring

Failures:

• test_abort.py: 3 failures (timing issues)
• test_batch_completion.py: 2 failures (tools not executing)
• test_tool_approval_race.py: 1 failure (execution count = 0)

Decision: Independent domains — abort logic separate from batch completion separate from race conditions

Dispatch:

Agent 1 → Fix test_abort.py
Agent 2 → Fix test_batch_completion.py
Agent 3 → Fix test_tool_approval_race.py

Results:

• Agent 1: Replaced timeouts with event-based waiting
• Agent 2: Fixed event structure bug (threadId in wrong place)
• Agent 3: Added wait for async tool execution to complete

Integration: All fixes independent, no conflicts, full suite green

Integration with pb-spec

• pb-build: Use when multiple independent tasks can be built concurrently (rare — pb-build is sequential by design)
• pb-improve: Parallelize audit subagents across categories
• Standalone: Use for any parallel investigation need